code: def make_pojo_embeddable(pojo_path):
      pojo_lines = []
      with open(pojo_path, "r") as pojo_file:
          pojo_lines = pojo_file.readlines()
          class_idx = next(
              filter(
                  lambda idx: pojo_lines[idx].startswith(
                      "public class"
                  ),
                  range(len(pojo_lines)),
              )
          )
          pojo_lines[class_idx] = pojo_lines[class_idx].replace(
              "public class", "class"
          )  # make package private
          pojo_lines = pojo_lines[class_idx - 1 :]
      return "".join(pojo_lines)
  
file_path: h2o-3/h2o-py/tests/testdir_generic_model/pyunit_pojo_import.py
imports: import h2o
  from h2o.estimators import H2OGradientBoostingEstimator, H2OGeneralizedLinearEstimator
  from tests import pyunit_utils
  import os
  import sys
  from pandas.testing import assert_frame_equal
label_desc: Use image node_id 4 for calling a global function with example usage: make_pojo_embeddable(pojo_path) and returns: str